Seasonal climate prediction for the Australian sugar industry using data mining techniques

McKinna, Lachlan, and Everingham, Yvette (2011) Seasonal climate prediction for the Australian sugar industry using data mining techniques. In: Kimito, Funatsu, and Hasegawa, Kiyoshi, (eds.) Knowledge-Oriented Applications in Data Mining. InTech, Rijeka, Croatia, pp. 109-126.

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Abstract

The ability to predict rainfall with adequate certainty and lead time is beneficial to both industry and public. Periods of high or low seasonal rainfall can have many follow on effects to agriculture, industry, public health and, water supply and management. In order to implement decisions, planning and management strategies to contend with these issues, the ability to predict seasonal rainfall quantities is of great importance (Klopper et al., 2006). Climate conditions are known to influence the cultivation of Sugarcane influencing planting, harvesting and milling (Muchow and Wood, 1996; Everingham et al., 2002; Jones and Everingham, 2005). Unforeseen climate events such as excessive rainfall, can adversely effect the agricultural practices related to Sugarcane cultivation. The Australian Sugarcane harvest period commences in May/June and aims to finish by November/December before the start of the rainy season (Everingham et al., 2002). The risk of excessive rainfall disrupting harvest operations is greatest towards the end of the sugarcane harvest period (Muchow and Wood, 1996; Everingham et al., 2002). Therefore, improved seasonal rainfall prediction during the October-December period is beneficial.

Item ID: 20785
Item Type: Book Chapter (Research - B1)
Additional Information:

All chapters in this book are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited.

ISBN: 978-953-307-154-1
Date Deposited: 22 Apr 2012 23:17
FoR Codes: 07 AGRICULTURAL AND VETERINARY SCIENCES > 0701 Agriculture, Land and Farm Management > 070104 Agricultural Spatial Analysis and Modelling @ 100%
SEO Codes: 82 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 8206 Harvesting and Packing of Plant Products > 820603 Sugar Cane (Cut for Crushing) @ 100%
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